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al-one

MCP Server for notify to weixin / telegram / bark / lark

Telegram send photo

tg_send_photo

Send photos via Telegram bot for notifications, supporting captions, reply threads, and multiple messaging platforms integration.

Instructions

Send photo via telegram bot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
photoYesPhoto URL
chat_idNoTelegram chat id, Default to get from environment variables
captionNoPhoto caption, 0-1024 characters after entities parsing
parse_modeNoMode for parsing entities in the caption. [text/MarkdownV2]
reply_to_message_idNoIdentifier of the message that will be replied to

Implementation Reference

  • The core handler function implementing the tg_send_photo tool logic. It sends a photo to a specified Telegram chat using the bot.send_photo method, handles optional caption with MarkdownV2 parsing, and returns the response as JSON.
    async def tg_send_photo(
        photo: str = Field(description="Photo URL"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        caption: str = Field("", description="Photo caption, 0-1024 characters after entities parsing"),
        parse_mode: str = Field("", description=f"Mode for parsing entities in the caption. [text/MarkdownV2]"),
        reply_to_message_id: int = Field(0, description="Identifier of the message that will be replied to"),
    ):
        if parse_mode == TELEGRAM_MARKDOWN_V2:
            caption = telegramify_markdown.markdownify(caption)
        res = await bot.send_photo(
            chat_id=chat_id or TELEGRAM_DEFAULT_CHAT,
            photo=photo,
            caption=caption or None,
            parse_mode=parse_mode if parse_mode in [TELEGRAM_MARKDOWN_V2] else None,
            reply_to_message_id=reply_to_message_id or None,
        )
        return res.to_json()
  • FastMCP decorator that registers the tg_send_photo function as a tool with title and description.
    @mcp.tool(
        title="Telegram send photo",
        description="Send photo via telegram bot",
    )
  • Registers all tools from tgbot module (including tg_send_photo) with the main MCP instance.
    tgbot.add_tools(mcp)
  • Creates the Telegram Bot instance shared across tg_send_photo and other Telegram tools.
    bot = Bot(
        TELEGRAM_BOT_TOKEN,
        base_url=f"{TELEGRAM_BASE_URL}/bot",
        base_file_url=f"{TELEGRAM_BASE_URL}/file/bot",
    ) if TELEGRAM_BOT_TOKEN else None
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Send photo via telegram bot' implies a write operation (sending), but it doesn't disclose critical traits: whether this requires authentication, rate limits, error handling, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste: 'Send photo via telegram bot'. It's appropriately sized and front-loaded, clearly stating the core function without unnecessary details. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, mutation operation) and lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error conditions, authentication needs, or behavioral constraints. For a tool that performs an external API call to send data, this minimal description leaves too many gaps for effective agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 5 parameters (photo, chat_id, caption, parse_mode, reply_to_message_id) with descriptions. The description adds no parameter-specific information beyond what's in the schema. According to rules, baseline is 3 when schema coverage is high (>80%) and no param info is added in description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Send photo via telegram bot' clearly states the action (send) and resource (photo) with the platform (Telegram bot). However, it doesn't differentiate from sibling tools like tg_send_message, tg_send_video, or tg_send_file, which all send different media types via the same platform. The purpose is clear but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose tg_send_photo over tg_send_message (for text) or tg_send_video (for videos), nor does it specify prerequisites like needing a Telegram bot token or chat setup. Usage is implied by the name but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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